Gender: Male 
Age: 35-44
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Christian 
Education: High school or below
Mother's education: Graduate degree
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 3
Home: Other (Please specify) Live with family
Employment: Not employed, but looking for work
Occupation: Prefer not to say
Mother's occupation: Prefer not to say
Father's occupation: Prefer not to say
Hobbies: Listen to rock/indie music;Watch sports;Exercise;Use social media 
Devices used daily: Smartphone;Other Desktop
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools they would find useful: Other (specify) None, don't have any issues with scarce performance
Frequency of LLM use: Sometimes
LLMs used: ChatGPT;Google Gemini;Microsoft Bing AI 
LLM use cases: Translation;Writing (e.g., composing emails);Proofreading/Editing (e.g., grammar, spelling, structure improvements);Solving math or logical problems;Generate art;Learning (e.g., explaining complex concepts in simple terms);Answering questions about general knowledge 
Contexts of LLM use: Learning;Personal 
Prompt 1: How to decide between two similar products
Prompt 2: Can you tell me how to politely ask someone if they still plan to do something
Prompt 3: How to talk to a doctor about an embarrassing issue
Prompt 4: What are some stiff thumb tendon exorcises
Prompt 5: How best to calculate risks
Prompt 6: How to estimate how many pennies in a 500ml jar
Prompt 7: Can you explain in simple terms how to adjust a bicycle derailleur